Microkinetic Modeling of Nanoparticle Catalysis using Density Functional Theory

Licentiate thesis, 2017

Heterogeneous catalysis is vitally important to modern society, and one path towards rational catalyst design is through atomistic scale understanding. The atomistic scale can be linked to macroscopic observables by microkinetic models based on first-principles calculations. With the increasing accuracy of first-principles methods and growing com- putational resources, it has become important to investigate and further develop the methodology of microkinetic modeling, which is the theme of this thesis. First, a procedure for mean-field microkinetic modeling of reactions over extended surfaces is developed, where complete methane oxidation over Pd(100) and Pd(111) is studied as an example. The model reveals how the main reaction mechanisms depend on reaction conditions, and shows poisoning as well as promotion phenomena. Second, the effect of entropy in microkinetic modeling is investigated, where CO oxidation over Pt(111) is used as a model reaction. Entropy is found to affect reaction kinetics substantially. Moreover, a method named Complete Potential Energy Sampling (CPES) is developed as a flexible tool for estimating adsorbate-entropy. Third, a kinetic Monte Carlo method is developed to bridge the materials gap in het- erogeneous catalysis. The computational cost to map out the complete reaction-energy- landscape on a nanoparticle is high, which is solved herein using generalized coordination numbers as descriptors for reaction energies. CO oxidation over Pt is studied, and nanoparticles are found to behave differently than the corresponding extended surfaces. Moreover, the active site is found to vary with reaction conditions. Finally, the reaction orders and apparent activation energies are coupled to the microscale via the degree of rate control, which enhances the atomistic understanding of reaction kinetics.